{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "加载canada数据集，构建RNN建模的基础数据集，提炼训练集与测试集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "src_canada = pd.read_csv(\"http://image.cador.cn/data/canada.csv\")\n",
    "tmp = src_canada.drop(columns=['year','season'])\n",
    "\n",
    "# 计算标准化操作对应的均值向量与标准差向量\n",
    "vmean = tmp.apply(lambda x:np.mean(x))\n",
    "vstd = tmp.apply(lambda x:np.std(x))\n",
    "\n",
    "# 对基础数据进行标准化处理\n",
    "t0 = tmp.apply(lambda x:(x-np.mean(x))/np.std(x)).values\n",
    "\n",
    "# 定义输入序列长度、输入与输出的维度\n",
    "SEQLEN = 6\n",
    "dim_in = 4\n",
    "dim_out = 4\n",
    "\n",
    "# 定义训练集与测试集的基础数据，并完成构建。这里使用最后8条数据进行测试\n",
    "X_train = np.zeros((t0.shape[0]-SEQLEN-8, SEQLEN, dim_in))\n",
    "Y_train = np.zeros((t0.shape[0]-SEQLEN-8, dim_out),)\n",
    "X_test = np.zeros((8, SEQLEN, dim_in))\n",
    "Y_test = np.zeros((8, dim_out),)\n",
    "for i in range(SEQLEN, t0.shape[0]-8):\n",
    "    Y_train[i-SEQLEN] = t0[i]\n",
    "    X_train[i-SEQLEN] = t0[(i-SEQLEN):i]\n",
    "for i in range(t0.shape[0]-8,t0.shape[0]):\n",
    "    Y_test[i-t0.shape[0]+8] = t0[i]\n",
    "    X_test[i-t0.shape[0]+8] = t0[(i-SEQLEN):i]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "基于keras构建RNN的网络结构"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.layers import SimpleRNN, Dense\n",
    "from keras.models import Sequential\n",
    "model = Sequential()\n",
    "model.add(SimpleRNN(128, input_shape=(SEQLEN, dim_in),activation='relu',recurrent_dropout=0.01))\n",
    "model.add(Dense(dim_out,activation='linear'))\n",
    "model.compile(loss = 'mean_squared_error', optimizer = 'rmsprop')\n",
    "history = model.fit(X_train, Y_train, epochs=1000, batch_size=2, validation_split=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对后面8条测试数据进行预测，并绘制对比图表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "# 以下 font.family 设置仅适用于 Mac系统，其它系统请使用对应字体名称\n",
    "matplotlib.rcParams['font.family'] = 'Arial Unicode MS'\n",
    "preddf=model.predict(X_test)*vstd.values+vmean.values\n",
    "m = 16\n",
    "xts = src_canada[['year','season']].iloc[-m:].apply(lambda x:str(x[0])+'-'+x[1],axis=1).values\n",
    "cols = src_canada.drop(columns=['year','season']).columns\n",
    "fig, axes = plt.subplots(2,2,figsize=(10,7))\n",
    "index = 0\n",
    "for ax in axes.flatten():\n",
    "    ax.plot(range(m),src_canada[cols].iloc[-m:,index],'-',c='lightgray',linewidth=2,label=\"real\")\n",
    "    ax.plot(range(m-8,m),preddf[:,index],'o--',c='black',linewidth=2,label=\"predict\")\n",
    "    ax.set_xticklabels(xts,rotation=50)\n",
    "    ax.set_ylabel(\"$\"+cols[index]+\"$\",fontsize=14)\n",
    "    ax.legend()\n",
    "    index = index + 1\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
